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This study aims to explore talent retention in knowledge-intensive industries by investigating the mediating processes between the existence and application of human resource management (HRM) and employee turnover. Toward this end, drawing on the conservation of resources and job demands–resources theories, a three-dimensional model is examined, which includes the relationship between HRM, knowledge management (KM) and change management (CM), as well as their relationship with employee engagement and employee turnover intention.

The proposed research model has been studied with a sample of 168 talented employees in over six European countries, using a quantitative approach, involving the structural equation modeling method. All data were gathered by a multidimensional questionnaire via prolific, an academic crowdsourcing platform.

Results indicated that knowledge-intensive services firms may achieve higher talent retention through the interaction of HRM with KM and CM practices, which may lead to enhanced employee engagement.

Possible limitations of the study include the relatively small sample size, the self-rate questions for the collection of data and the use of cross-sectional data.

To retain their talented employees, organizations should identify ways to improve their HRM, CM and KM practices. In addition, HR practitioners ought to include their talented employees in all organizational change and KM processes and create mechanisms that successfully support knowledge acquisition, creation, sharing, retention and codification.

To the best of the authors’ knowledge, this is the first study to examine various factors of retaining talented employees in knowledge-intensive services. Furthermore, the study took place in six European countries, i.e. UK, Poland, Italy, Germany, Portugal and Greece, where the research on talent retention is very limited.

Generative AI and more specifically ChatGPT has brought a revolution in the lives  of people by providing them with required knowledge that it has learnt from an exponentially large knowledge base. In this viewpoint, we are initiating the debate and offer the first step towards Generative AI based knowledge management systems in organizations.

This study is a viewpoint and develops a conceptual foundation using existing literature on how ChatGPT can enhance the KM capability based on Nonaka’s SECI model. It further supports the concept by collecting data from a public sector univesity in Hong Kong to strenghten our argument of ChatGPT mediated knowledge management system.

We posit that all four processes, that is Socialization, Externalization, Combination and Internalization can significantly improve when integrated with ChatGPT. ChatGPT users are, in general, satisfied with the use of ChatGPT being capable of facilitating knowledge generation and flow in organizations.

The study provides a conceptual foundation to further the knowledge on how ChatGPT can be integrated within organizations to enhance the knowledge management capability of organizations. Further, it develops an understanding on how managers and executives can use ChatGPT for effective knowledge management through improving the four processes of Nonaka’s SECI model.

This is one of the earliest studies on the linkage of knowledge management with ChatGPT and lays a foundation for ChatGPT mediated knowledge management system in organizations.

Fish quarantine is a measure to prevent the entry and spread of quarantine fish pests and diseases abroad and from one area to another within Indonesia's territory. Based on these backgrounds, this study aims to identify the knowledge, knowledge management (KM) processes and knowledge management system (KMS) priority needs for quarantine fish and other fishery products measures (QMFFP) and then develop a classification model and web-based decision support system (DSS) for QMFFP decisions.

This research methodology uses combination approaches, namely, contingency factor analysis (CFA), the cross-industry standard process for data mining (CRISP-DM) and knowledge management system development life cycle (KMSDLC). The CFA for KM solution design is performed by identifying KM processes and KMS priorities. The CRISP-DM for decision classification model is done by using a decision tree algorithm. The KMSDLC is used to develop a web-based DSS.

The highest priority requirements of KM technology for QMFFP are data mining and DSS with predictive features. The main finding of this study is to show that web-based DSS (functions and outputs) can support and accelerate QMFFP decisions by regulations and field practice needs. The DSS was developed using the CTree algorithm model, which has six main attributes and eight rules.

This study proposes a novel comprehensive framework for developing DSS (combination of CFA, CRISP-DM and KMSDLC), a novel classification model resulting from comparing two decision tree algorithms and a novel web-based DSS for QMFFP.

This study aims to extend and explore patterns and trends of research in the linkage of big data and knowledge management (KM) by identifying growth in terms of numbers of papers and current and emerging themes and to propose areas of future research.

The study was conducted by systematically extracting, analysing and synthesizing the literature related to linkage between big data and KM published in top-tier journals in Web of Science (WOS) and Scopus databases by exploiting bibliometric techniques along with theory, context, characteristics, methodology (TCCM) analysis.

The study unfolds four major themes of linkage between big data and KM research, namely (1) conceptual understanding of big data as an enabler for KM, (2) big data–based models and frameworks for KM, (3) big data as a predictor variable in KM context and (4) big data applications and capabilities. It also highlights TCCM of big data and KM research through which it integrates a few previously reported themes and suggests some new themes.

This study extends advances in the previous reviews by adding a new time line, identifying new themes and helping in the understanding of complex and emerging field of linkage between big data and KM. The study outlines a holistic view of the research area and suggests future directions for flourishing in this research area.

This study highlights the role of big data in KM context resulting in enhancement of organizational performance and efficiency. A summary of existing literature and future avenues in this direction will help, guide and motivate managers to think beyond traditional data and incorporate big data into organizational knowledge infrastructure in order to get competitive advantage.

To the best of authors’ knowledge, the present study is the first study to go deeper into understanding of big data and KM research using bibliometric and TCCM analysis and thus adds a new theoretical perspective to existing literature.

The main objective of this work is to design a statistical multiple regression model that helps to empirically explain the impact of economic incentives, management style, emotional health and research activities on university professors in northern Mexico and their perception of happiness.

In this research, the authors analysed the correlation between happiness perception and four independent variables divided into two dimensions: 1. individual dimensions: emotional health and research activities and 2. organisational dimensions: economic incentives and management styles. A questionnaire was developed, tested and analysed for this matter. The authors applied this instrument to 384 university professors of both genders among 1301 in the region.

Using correlational analysis, the authors confirm a strong and statically significant relationship between all variables. It is also no evidence of multicollinearity. Finally, by applying multiple regression analysis, it was accepted that all independent variables have significance in explaining the emergence of personal happiness (R2 = 42%). Finally, the predictive equation presents possible results with values that confirm the effectiveness of the theoretical model. Results indicate that happiness perception is related to independent variables, with economic incentives being the most vital relationship.

This study's limitations are that the novel perspective of the explanatory variables of economic incentives, emotional health, management style and research activities needs additional confirmatory studies. Therefore, the authors need to perform studies with new explanatory perspectives. Another limitation of the study may be considering a cross-sectional and not a longitudinal model. This study considered it more appropriate to analyse the explanatory variables that influence and are the outcome of happiness perception for the data collected. Finally, it is essential to highlight that this research has been conducted in an underdeveloped country. Thus, it should consider conducting subsequent confirmatory studies in similar settings and other types of economies, such as in a developed country.

This paper explains the relevance of two-dimensional activities in the happiness perception of professors. As other studies mention, productivity is correlated to happiness, and production outcomes could be improved if the schools implement policies to promote this perception. Happiness could be a solid strategy to improve academic outcomes, and the results propose several actions to achieve this goal.

This paper addresses an important activity of professors from a perspective of happiness perception. Thus, putting the professor as the leading relevant agent in schools, the authors propose a multivariate analysis of the outcomes of professors' jobs. Both the schools and the professors have their own goals at their own levels. If policies are created based on persons, in this case, professors, to improve organizational goals, then it might profoundly impact social actions inside the schools.

This paper increases the literature on happiness perception studies and proposes the examination of the relationship between perceived personal happiness and dimensions that influence this perception; these are from two kinds: 1. individual dimensions: emotional health and research activities and 2. organisational dimensions: economic incentives and management styles, which is an original approach and open discussion to further new approaches to this study.

This study investigates the impact of entrepreneurial orientation (EO) and knowledge management (KM) on firm performance (PERF), as well as the mediating role of KM in the EO–PERF (EO-PERF relationship). In particular, this study aims to explain the impact of KM on the relationship between the EO dimensions and PERF; dimensions are risk-taking (RT), innovativeness (IN) and proactiveness (PR).

This study uses structural equation modelling and fuzzy-set qualitative comparative analysis (fsQCA) methodologies to explore target relationships. The sample consists of 150 small furniture manufacturers operating in Poland (out of 1,480 in the population).

The study findings show that KM partially mediates the IN–PERF relationship. Furthermore, fsQCA reveals that KM accompanied by IN is a core condition that leads to PERF. Moreover, the absence of KM (accompanied by the absence of RT and IN) leads to the absence of PERF. In addition, the results show that all the variables examined (RT, IN, PR and KM) positively impact PERF.

This study explores the role of KM in the context of EO and its impact on PERF in the low-tech industry. The study uses simultaneously two methodologies that represent different approaches in the search for the expected relationships. The findings reveal that KM mediates the EO-PERF relationship.

The ongoing paradigm shift in the energy sector holds paramount implications for the realization of the sustainable development goals, encompassing critical domains such as resource optimization, environmental stewardship and workforce opportunities. Concurrently, this transformative trajectory within the power sector possesses a dual-edged nature; it may ameliorate certain challenges while accentuating others. In light of the burgeoning research stream on open innovation, this study aims to examine the intricate dynamics of knowledge-based industry-university-research networking, with an overarching objective to elucidate and calibrate the equilibrium of ambidextrous innovation within power systems.

The authors scrutinize the role of different innovation organizations in three innovation models: ambidextrous, exploitative and exploratory, and use a multiobjective decision analysis method-entropy weight TOPSIS. The research was conducted within the sphere of the power industry, and the authors mined data from the widely used PatSnap database.

Results show that the breadth of knowledge search and the strength of an organization’s direct relationships are crucial for ambidextrous innovation, with research institutions having the highest impact. In contrast, for exploitative innovation, depth of knowledge search, the number of R&D patents and the number of innovative products are paramount, with universities playing the most significant role. For exploratory innovation, the depth of knowledge search and the quality of two-mode network relations are vital, with research institutions yielding the best effect. Regional analysis reveals Beijing as the primary hub for ambidextrous and exploratory innovation organizations, while Jiangsu leads for exploitative innovation.

The study offers valuable implications to cope with the dynamic state of ambidextrous innovation performance of the entire power system. In light of the findings, the dynamic state of ambidextrous innovation performance within the power system can be adeptly managed. By emphasizing a balance between exploratory and exploitative strategies, stakeholders are better positioned to respond to evolving challenges and opportunities. Thus, the study offers pivotal guidance to ensure sustained adaptability and growth in the power sector’s innovation landscape.

The primary originality is to extend and refine the theoretical understanding of ambidextrous innovation within power systems. By integrating several theoretical frameworks, including social network theory, knowledge-based theory and resource-based theory, the authors enrich the theoretical landscape of power system ambidextrous innovation. Also, this inclusive examination of two-mode network structures, including the interplay between knowledge and cooperation networks, unveils the intricate interdependencies between these networks and the ambidextrous innovation of power systems. This approach significantly widens the theoretical parameters of innovation network research.

This study examines the marketing performance of firms from an international dynamic marketing capability perspective. It also investigates the moderating role of marketing leadership teams to improve organizations' international marketing performance.

The authors used dynamic capability view and other related literature to develop a theoretical model, which was validated with the structural equation modelling technique, considering a sample of 455 respondents from Indian firms. The authors also used the multigroup analysis method to examine the moderating impacts of a firm's marketing leadership team on their international marketing performance.

There is a positive relationship between a firm's dynamic ability factors and its international dynamic-marketing capabilities. The study also finds that a firm's marketing leadership team has a significant positive moderating impact on improving its international marketing performance.

The unique theory-based model clearly explains how a firm's dynamic abilities impact international dynamic marketing capability, which then impacts its international marketing performance. This model can help practitioners, researchers and academicians to understand the significance of a firm's international dynamic capability on international marketing performance. The study also helps firms to understand the moderating influence of marketing leadership teams to improve international marketing performance.

This study adds value to the body of literature on international dynamic marketing, international marketing performance and international marketing knowledge management, on which, until now, few other studies have focused. Thus, this research is unique. The proposed model of international dynamic marketing is also unique with high explanative power.

The purpose of this study is to examine the link between knowledge-oriented leadership (KOL) and organizational performance (OP) at Higher Education Institutions (HEIs) both directly and indirectly through service innovation and knowledge-sharing quality.

This research used Smart PLS 4.0 to model structural equations using a sample comprising 237 academic staff from HEIs in China.

According to the study data, KOL has a negligible direct influence on organizational performance. The link between KOL and OP, on the other hand, is entirely mediated by the quality of knowledge sharing quality and service innovation.

The study results validate universities' experience with KOL and propose ways for academics at higher education institutions to prioritize the quality of knowledge sharing and service innovation, which in turn helps organizations function better in a volatile environment.

Despite the growing relevance of knowledge-oriented leadership in higher education, little research has been conducted to examine the mediating impact of numerous factors in the link between KOL and OP. The present research examines the link between knowledge-oriented leadership, the quality of knowledge sharing, service innovation and the performance of higher education institutions. The current study scientifically investigates the link between KOL and OP and offers insight into the existing literature by examining the mediating role of KSQ and SI.

This study examines how the characteristics of innovation knowledge exchanged among affiliate firms affect the ownership strategies adopted for their foreign subsidiaries.

This study employs a cross-classified multilevel model to examine a sample of 185 Korean manufacturing affiliates derived from 49 Chaebols engaged in international diversification, along with their 1,110 foreign manufacturing subsidiaries.

While exploratory innovation knowledge exchange lowers the affiliate's level of ownership in its foreign subsidiary, exploitative innovation knowledge exchange rather increases the affiliate's level of ownership in its foreign subsidiary.

This study advances the literature on intrafirm knowledge exchange by highlighting it as a determinant of ownership strategies. The study further shows that the characteristics of knowledge exchanged at the affiliate level not only determine the ownership structure but also have the potential to shape the direction in which the subsidiary develops its competencies.

This study has practical implications for the managers of business group affiliates. The results suggest that managers should adapt their ownership strategies according to the type of knowledge exchanged at the affiliate level to achieve a balanced and synergistic effect on intraorganizational knowledge exchange.

Previous studies have extensively explored the performance implications related to knowledge exchange. However, there is a notable gap in understanding the mechanisms through which the value of knowledge transferred within an affiliate is realized. To address this gap, this study focuses on ownership strategy as a crucial factor and empirically examines how the characteristics of innovation knowledge exchanged among affiliate firms influence the ownership strategies adopted for their foreign subsidiaries. By investigating this relationship, this study provides valuable insights into the complex dynamics of knowledge exchange and its effect on ownership decisions within business group affiliates.